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<p>Drought is a recurring natural hazard that severely reduces the availability of water in semi-arid regions. Water scarcity intensifies social inequalities, undermines agricultural productivity, and increases public health risks. Allocating resources strategically mitigates these effects by targeting critical areas to maximize the benefits of interventions. This study proposes a group multi-criteria sorting model for allocating water resources during drought. This study seeks to assist decision-makers (DMs) in prioritizing municipalities using a fair, transparent framework. The model integrates the PROMETHEE-ROC method with partial-information procedures to define parameters. Three government DMs evaluated eight water, sanitation, environmental, and socio-economic criteria. Twenty-three municipalities in Pernambuco, Brazil, were sorted into categories of High, Moderate, and Low criticality. The findings indicate three municipalities (13%) require immediate intervention, fifteen (65%) require moderate attention, and five (22%) have lower criticality. Sensitivity analysis confirms stable sorting in more than 60% of simulations. Thus, the model enhances decision-making efficiency, minimizes conflicts, and provides a structured tool to prioritize action plans based on real-world conditions.</p>

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Multi-Criteria Sorting Model for Water Resource Allocation in Drought Regions

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年3月28日

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  • Gabriel de Oliveira Castro,
  • Danielle Costa Morais

摘要

Drought is a recurring natural hazard that severely reduces the availability of water in semi-arid regions. Water scarcity intensifies social inequalities, undermines agricultural productivity, and increases public health risks. Allocating resources strategically mitigates these effects by targeting critical areas to maximize the benefits of interventions. This study proposes a group multi-criteria sorting model for allocating water resources during drought. This study seeks to assist decision-makers (DMs) in prioritizing municipalities using a fair, transparent framework. The model integrates the PROMETHEE-ROC method with partial-information procedures to define parameters. Three government DMs evaluated eight water, sanitation, environmental, and socio-economic criteria. Twenty-three municipalities in Pernambuco, Brazil, were sorted into categories of High, Moderate, and Low criticality. The findings indicate three municipalities (13%) require immediate intervention, fifteen (65%) require moderate attention, and five (22%) have lower criticality. Sensitivity analysis confirms stable sorting in more than 60% of simulations. Thus, the model enhances decision-making efficiency, minimizes conflicts, and provides a structured tool to prioritize action plans based on real-world conditions.